Venue recommendations based on shared guest traits

ABSTRACT

A platform identifies that a first venue attendee is similar to a second venue attendee based on at least one shared trait. The platform identifies an indicator of positivity about a particular point of interest corresponding to the second venue attendee. The platform selects the particular point of interest as a recommended point of interest for the first venue attendee based on the similarity between the first venue attendee and the second venue attendee and the indicator of positivity about the particular point of interest corresponding to the second venue attendee.

CROSS-REFERENCE TO RELATED APPLICATIONS

The present application is a continuation-in-part of U.S. applicationSer. No. 15/828,120 filed Nov. 30, 2017 and entitled “Development,Deployment and Real Time Management of Highly Personalized ExperiencesOccurring at Managed Locations,” and claims the priority benefit of U.S.provisional application No. 62/428,303 filed Nov. 30, 2016 and entitled“Development, Deployment and Real Time Management of Highly PersonalizedExperiences Occurring at Managed Locations,” the disclosures of whichare hereby incorporated by reference.

BACKGROUND 1. Field

The present teachings are generally related to an experience developmentand management platform. More specifically, the present teachings relateto development, deployment and real time management of highlypersonalized experiences occurring at managed locations.

2. Description of the Related Art

Locations that host visitors provide a wide range of experiences. Thevenues often have special events such as entertainment performances,provide attractions, such as rides, and provide various goods andservices, including foods, beverages, souvenirs and other merchandise,and many others. Items available at any given point of interest within alocation often change throughout a day or season, and other changingfactors, such as waiting lines, can further impact a guest or customerexperience. In such a complex and changing environment, it is verydifficult to provide visitors with relevant information at all times asthe visitors move from point-to-point within the location managed by ahost. Also, as many venues are large and complex, challenges exist forpersonnel to keep track of what is happening throughout a location at agiven time and to help each visitor have a favorable experiencethroughout a visit, and challenges exist for visitors to communicateamong themselves or communicate with the personnel of a venue. Mostlocations that host these experiences provide static paper maps,brochures or signs that provide guests information about a location andencourage engagement in one or more activities at the location. Someprovide additional information via website or apps that contain generalinformation about the venue and some updated information, such as eventschedules.

However, the quantity of experiences and points of interest at venuescan be overwhelming for venue attendees. Information concerning theseexperiences and points of interest can be difficult or impossible forattendees to find, as not all of it is publically accessible, and anyinformation that is available might be difficult to parse in anymeaningful way. As such, attendees, especially in groups, often mustspend long periods of time deliberating and planning routes anditineraries that makes sense based on their locations, their likes,their dislikes, and so forth—and even so, they still might make poorchoices in light of missing inventory at restaurants, long queues atcertain points of interest, or other discouraging situations. As such, asystem is needed to intelligently make recommendations to users and togroups of users based on different types of information about a venueand the user(s).

SUMMARY

A method for itinerary personalization for a first venue attendee in apredetermined event venue area is claimed. The method includesreceiving, from a mobile device associated with the first venueattendee, a location of the mobile device associated with the firstvenue attendee. The method also includes retrieving a plurality of venueattendee profiles including at least a first venue attendee profilecorresponding to the first venue attendee and a second venue attendeeprofile corresponding to a second venue attendee, wherein each venueattendee profile identifies a plurality of traits about one of theplurality of venue attendees. The method also includes identifying thatthe first venue attendee is similar to the second venue attendee basedon identifying at least a first shared trait common to both the firstvenue attendee profile and the second venue attendee profile. The methodalso includes retrieving locations of a plurality of points of interestlocated within the predetermined event venue area. The method alsoincludes selecting a recommended point of interest for the first venueattendee from the plurality of points of interest based on therecommended point of interest being within a predetermined range of thelocation of the mobile device associated with the first venue attendeeand based on identifying an indicator of positivity associated with therecommended point of interest and corresponding to the second venueattendee. The method also includes sending at least the recommendedpoint of interest to the mobile device associated with the first venueattendee.

A system that generates a personalized itinerary for a venue attendee ina predetermined event venue area is claimed. The system includes acommunication transceiver that receives a location of a mobile deviceassociated with the first venue attendee and sends a recommended pointof interest to the mobile device associated with the first venueattendee. The system also includes a memory storing instructions,locations of a plurality of points of interest located within thepredetermined event venue area, and a plurality of venue attendeeprofiles including at least a first venue attendee profile correspondingto the first venue attendee and a second venue attendee profilecorresponding to a second venue attendee, wherein each venue attendeeprofile identifies a plurality of traits about one of the plurality ofvenue attendees. The system also includes a processor, wherein executionof the instructions by the processor causes the processor to performsystem operations. The system operations include identifying that thefirst venue attendee is similar to the second venue attendee based onidentifying at least a first shared trait common to both the first venueattendee profile and the second venue attendee profile and selecting therecommended point of interest for the first venue attendee from theplurality of points of interest based on the recommended point ofinterest being within a predetermined range of the location of themobile device associated with the first venue attendee and based onidentifying an indicator of positivity associated with the recommendedpoint of interest and corresponding to the second venue attendee.

Another method for generating a personalized itinerary for a venueattendee in a predetermined event venue area is claimed. The methodincludes receiving a location of a mobile device associated with thefirst venue attendee. storing profile information identifying a firstplurality of traits of the first venue attendee and a second pluralityof traits of a second venue attendee. The method also includesidentifying a first shared trait that is common to both the firstplurality of traits and the second plurality of traits. The method alsoincludes storing locations of a plurality of points of interest locatedwithin the predetermined event venue area. The method also includesselecting a recommended point of interest from the plurality of pointsof interest based on identifying an indicator of positivity about therecommended point of interest corresponding to the second venueattendee, wherein the recommended point of interest is within apredetermined range of the location of the mobile device associated withthe first venue attendee. The method also includes sending at least therecommended point of interest to the mobile device associated with thefirst venue attendee.

BRIEF DESCRIPTION OF THE FIGURES

FIG. 1 illustrates a system architecture for personalizing journeys anditineraries.

FIG. 2 illustrates a technology stack for real-time management ofexperiences with respect to personalized itineraries.

FIG. 3 illustrates information flow for real-time management ofexperiences and personalized itineraries.

FIG. 4 illustrates a dynamic live venue map identifying a personalizeditinerary in a theme park venue.

FIG. 5 illustrates a recommended itinerary map interface for a singleuser.

FIG. 6 illustrates a recommended itinerary map interface for two users.

FIG. 7 illustrates delivery of itinerary personalization to users.

FIG. 8 is a block diagram of an exemplary computing device that may beused to implement the present systems.

FIG. 9 illustrates identification of similar users based on sharedtraits.

FIG. 10 illustrates a recommended itinerary map interface for two usersin which certain recommendations are generated based on similarities toother users.

DETAILED DESCRIPTION

A platform is described herein with various methods, systems,components, processes, services and the like that facilitate the design,creation, delivery and management of experiences at locations and venuesthat are optionally managed by a host. The platform generates apersonalized itinerary and corresponding map for a user within a venue.The personalized itinerary includes at least one recommended point ofinterest, the recommendation generated based on a location of therecommended point of interest relative to a location of the user, andbased on a comparison between user profile information concerning theuser and point of interest information concerning the recommended pointof interest. The recommended point of interest may also be recommendedbased on estimated wait times, queue lengths, or other informationobtained by the platform's servers.

Locations, areas, or venues as described herein may includeentertainment venues, malls, stores, theme parks, campuses, cruiseships, schools, universities, arenas, public parks, resorts, airports,terminals, tourist attractions, monuments, stations, markets, districts(e.g., municipal districts), stadiums, predetermined geographical areas,cruise routes, travel routes, cities, counties, countries, continents,or a combination thereof. These and other locations are collectivelyreferred to throughout this disclosure interchangeably as “venues,”,“areas,” or “locations,” and reference to any of the foregoing should beunderstood to encompass one or more of these, except where contextindicates otherwise. Such locations, areas, or venues are hosted byparties such as commercial enterprises, non-profit entities, educationalentities, and federal, state and municipal governments, collectivelyreferred to herein as “hosts,” “managers,” or “owners.” Such locationsattract and host thousands of people (referred to herein as “visitors,”“guests,” and “customers”) and provide a wide range of experiences. Suchlocations, areas, or venues may have predetermined boundaries that maybe used as geofence boundaries that, when crossed by a location-trackingdevice whose location is determined via Global Navigation SatelliteSystem (GNSS) or proximity to short-range wireless beacon devices, maytrigger actions as described further herein.

The platform of the present disclosure enables the creation ofpersonalized, relevant experiences that are delivered to guests at oneor more points of interest within a location at the right time, takinginto account a wide range of dynamic factors. By delivering a series ofsuch experiences over the course of a visit, through a dynamic,personalized itinerary, a host can provide guests with an optimizedoverall experience while using the resources that are required toprovide such experiences more efficiently and more profitably.

The present disclosure further includes a wide range of systems,methods, components, processes, and the like that facilitate thedevelopment and operation of the platform. For example, the platform mayinclude methods and systems for developing and managing a user profileor identity, such as based on demographic factors, past history, anduser behavior, such as to enable provision of personalized experiences,recommendations, itineraries and communications. The platform mayinclude facilities for automating the creation, assembly, delivery, andmanagement of experiences, including facilities for connecting to andintegrating with relevant systems (such as inventory systems, ticketingand entitlement management systems, reservations systems, schedulingsystems, and many others), for extracting, transforming and loading datato and from such systems, and for using machine learning to automate thecompletion of various methods, such as generation of relevantrecommendations, customization of communications, optimization ofmonetization, optimization of experiences, optimization of itineraries,and others.

The platform may further include various methods for facilitatingcommunication among hosts, personnel and visitors. These methods includedetermining that a user has entered a managed location by a computingdevice and identifying user contacts within the venue. The methodsfurther include transmitting messages and other content to computingdevices associated with each user contact within the venue regarding theuser within the venue.

The present teachings further include methods for providing a dynamicmap that is configured for display on a computing device, includingproviding graphical images of a venue and of relevant points of interestwithin the venue, with various interface elements, such as icons, logos,directional indicators, and the like that facilitate understanding aboutthe venue. The map may provide a navigation interface, such as forrouting a user to one or more points of interest in a location, such asguiding a user through one or more steps of an itinerary. The map mayfurther include providing a visual update of the user on the map as thevisitor moves through the venue and providing a personalized message orother content to the visitor regarding the venue, such as based on userdata collected while the user is in the venue or other information aboutthe user.

The present teachings also include methods for determining wait timesand using wait time information as a factor for designing and deliveringexperiences. The methods may include receiving direct wait time data fora point of interest, receiving location map data, and receivingadditional data including at least one of network traffic measurementdata, entitlement redemption data, and show or event schedule data. Themethods may further include determining a wait time and reporting thewait time to a remote device.

The present teachings may further include methods for engaging with auser within a venue. The method may include setting a first rule for apromotion provided by an application executing on a server. The firstrule may indicate to which users within a venue the promotion will beavailable. The method may further include communicating the promotion toa plurality of user devices within the venue and that correspond to thefirst rule. The user devices may be associated with users within thevenue. The method may also include updating the promotion before thepromotion ends for at least one of the plurality of users.

The terms “a” or “an,” as used herein, are defined as one or more thanone. The term “another,” as used herein, is defined as at least a secondor more. The terms “including” and/or “having”, as used herein, aredefined as comprising (i.e., open transition).

The present teachings generally include design, creation, development,assembly, provisioning, delivery and management of one or morepersonalized, timely experiences at one or more points of interest inone or more managed or hosted locations. For convenience these and otherelements and capabilities of the platform are collectively referred toherein as “management” or “real time management” of experiences, exceptwhere context indicates otherwise. A managed location can include any ofa wide variety of locations or venues as disclosed throughout thisdisclosure or known by those of skill in the art, such as a venue,stadium, arena, public park, public space or district, concert hall,amusement park, theme park, water park, block party, house party, beergarden, mall, store, monument, tourist attraction, and many others.Managed locations can also include multiple premises that as a whole canconstitute managed locations, such as, without limitation, a series offranchised locations. Managed locations can also include mobileplatforms such as watercraft, cruise liners, trains, and aircraft. Itwill be appreciated in light of the disclosure that an entertainmentvenue, such as a theme park, is but one managed location in which thepresent teachings can be implemented. Managed locations can also includelocations (one or many) of an enterprise, brand or other entity wherephysical assets of the enterprise are located. Managed locations canalso include any venue, store location, mall, theme park, city park,village, campus, cruise ship dock, airport terminals, parkingstructures, and many others.

The platform herein identifies that a first venue attendee is similar toa second venue attendee based on at least one shared trait. The platformidentifies an indicator of positivity about a particular point ofinterest corresponding to the second venue attendee. The platformselects the particular point of interest as a recommended point ofinterest for the first venue attendee based on the similarity betweenthe first venue attendee and the second venue attendee and the indicatorof positivity about the particular point of interest corresponding tothe second venue attendee.

FIG. 1 illustrates a system architecture for personalizing journeys anditineraries. Uses of the system 100 of FIG. 1 may include live, dynamicmapping that utilizes branding, including hyper-local marketing. Thesystem 100 of FIG. 1 includes an ecosystem of data sources 105 such asmobile devices and/or wearable devices 110, point-of-entry/-exit (POE)terminals 115, point-of-sale (POS) terminals 117, and databases 120.Communicatively coupled to data sources 105 are back-end applicationservers 125. In system 100, application servers 125 can ingest,normalize and process data collected from mobile devices 110 and variousPOS or POE terminals 115. Types of information 140 gathered from datasources 105 and processed by back-end application servers 125 aregenerally inclusive of identity information such as user profiles,customer relationship management (CRM) data, entitlements, demographics,reservation systems and social media sources like Pinterest™ andFacebook™ data. Information 140 gathered from data sources 105 andprocessed by back-end application servers 125 also includesproximity/location information gathered using GNSS receivers such asGlobal Positioning System (GPS) receivers of mobile/wearable devices 100and/or via proximity between mobile/wearable devices 100 and beaconsthat emit short-range wireless signals (e.g., Bluetooth®, Bluetooth® LE,iBeacon, NFC, RFID, WiFi, radio). Information 140 gathered from datasources 105 and processed by back-end application servers 125 alsoincludes time-related data, such as schedules, weather, and queuelength.

Mobile and wearable devices 110 can execute applications via processorsthat make use of sensors and receivers of the respective mobile andwearable devices 110 to generate customer engagement data and then sharethat customer engagement data as the information 140 to the applicationserver(s) 125. The customer engagement data/information 140 may include,for example, current and prior physical locale within a venue as well aswait times and travel times (e.g., how long was a customer at aparticular point in a venue and how long did it take the customer totravel to a further point in a venue), paths to certain point on themap, and other information. Mobile devices 110 are inclusive of wearabledevices. Wearable devices (or ‘wearables’) are any type of mobileelectronic device that can be worn on the body or attached to orembedded in clothes and accessories of an individual, such aswristwatches, wristbands, armbands, chest bands, ankle bands, glasses,head-worn devices, devices integrated into clothing (including shoes,pants, shirts, jackets, hats, and others), and others. Processors andsensors associated with a wearable can gather, process, display, andtransmit and receive information, including location information, motioninformation and physiological information, among many other types.

With continued reference to FIG. 1, the POS data may be gathered atpoint of entry (POE) 115, or point of sale (POS) terminals 117 that mayinteract with a mobile or wearable device 110 to track customer purchasehistory at a venue or preference for engagement at a particular localewithin the venue. POE terminals 115 may provide data related to venuetraffic flow, including entry and exit data that can be inclusive oftime and volume. POE terminals 115 may likewise interact with mobile andwearable devices 110. POE terminals 115 and POS terminals 117 alike mayinclude or be connected to beacon devices using short-range wirelesscommunication transceivers to communicate with the mobile and wearabledevices 110 and thereby determine a location of the mobile and wearabledevices 110 (or velocity, or heading, or other information 140concerning the mobile and wearable devices 110) relative to knownlocation of the beacon based on a known signal strength (and a knownsignal range at the known signal strength) of the beacon.

Historical data may also be accessed at databases 120 as a part of theapplication server 125 processing operation. The results of a processingor normalization operation may likewise be stored for later access anduse. Processing and normalization results may also be delivered tofront-end applications (and corresponding application servers) thatallow for the deployment of contextual experiences and provide a networkof services to remote devices as is further described herein.

The present system 100 may be used with and communicate with any numberof external front-end devices 135 by way of a communications network130, either directly through the communication network 130 or softwaredevelopment kit (SDK) instructions called by particular softwareapplications (e.g., white label apps) run at the app server(s) 125, atthe front-end devices 135, at the data sources 105, at a device alongthe way in the communication network 130, or some combination thereof.The communications network 130 may be a local, proprietary network(e.g., an intranet) and/or may be a part of a larger wide-area network.The communication network 130 may include a variety of connectedcomputing devices that provide one or more elements of a network-basedservice. The communications network 130 may include actual serverhardware or virtual hardware simulated by software running on one ormore actual machines thereby allowing for software controlled scaling ina cloud environment.

The communications network 130 may allow for communication between datasources 105 and front-end devices 135 via any number of variouscommunication paths or channels that collectively make up thecommunications network 130. Such paths and channels may operateutilizing any number of standards or protocols including TCP/IP, 802.11,Bluetooth, iBeacon, GSM, GPRS, 4G, and LTE. The communications network130 may be a local area network (LAN) that can be communicativelycoupled to a wide area network (WAN) such as the Internet operatingthrough one or more network service provider.

Information received and provided over a communications network 130 maycome from other information systems such as GPS, cellular serviceproviders, or third-party service providers such as social networks. Thesystem 100 can measure location and proximity using hardware on a userdevice (e.g., GPS) or collect the data from fixed hardware andinfrastructure such as Wi-Fi positioning systems and Radio Frequency ID(RFID) readers. An exemplary location and proximity implementation mayinclude a Bluetooth low-energy or iBeacon beacon with real timeproximity detection that can be correlated to latitude/longitudemeasurements for fixed beacon locations.

Additional use cases may include phone-based, GPS, real-time location(latitude/longitude) measurements, phone geo-fence-real timenotifications when a device is moving into or out of location regions,Wi-Fi positioning involving user location detection based on Wi-Fisignal strength (both active or passive), RFID/Near Field Communication(NFC), and cellular tower positioning involving wide range detection ofuser device location, which may occur at the metro-level.

Front-end devices 135 are inclusive of kiosks, mobile devices, wearabledevices, venue devices, captive portals, digital signs, and POS and POEdevices. It should be noted that each of these external devices may beused to gather information about one or more consumers at a particularlocation during a particular time. Thus, a device that is providinginformation to a customer on the front-end (i.e., a front-end device135) such as a mobile device executing an application or a speciallydesigned wearable can also function as a data source 105 as describedabove. In some cases, front-end devices 135 may include any one of thedata sources 105 providing the information 140 to the app server 125,such as one of the mobile/wearable devices 110, one of the points ofexit/entry 115, one of the points of sale 117, or one of the databases120.

The system 100 of FIG. 1 provides services for personalizing journeysand itineraries. For example, a dynamic map including markerscorresponding to various captured photos, recorded videos, transactionreceipts, messages, social media posts, and other events may begenerated at a mobile computing device 110, at one or more applicationserver(s) 125, at one or more front-end-devices 135, or some combinationthereof. Any of the devices illustrated in FIG. 1, including the mobilecomputing devices 110, application server(s) 125, and front-end devices135 may include at least one computing system 800, or may include atleast some of the components illustrated in FIG. 8.

FIG. 2 illustrates a technology stack for real-time management ofexperiences with respect to personalized itineraries. More specifically,FIG. 2 depicts a physical world content management system 200. Thephysical world content management system 200 can include a dynamic venuemap 202 and various elements of a venue systems infrastructure 204. Themanagement system 200 can also include a mobile device 220 and awearable device 222. The management system 200 can also manage variousitineraries 228, such as for users or groups of users. The managementsystem 200 can include an experience as a service (EaaS) platform 230with a wide range of capabilities, as well as facilities for variousinterfaces to the platform 230, such as interfaces for analytics 256 andfor other users of an enterprise, such as through a corporate orcommercial viewer 254. The management system 200 may also include anEaaS software development kit (SDK) 250 for designing, developing andassembling experiences. The management system 200 can further include alive experience development application 252 for developing experiences.

The EaaS platform 230 of FIG. 2 may be run via the app server(s) 125 ofFIG. 1. The mobile device 220 and wearable device 222 of FIG. 2 may actas the mobile/wearable device 110 of FIG. 1 and/or the front-end device135 of FIG. 1. The locations system infrastructure 204 of FIG. 2 mayinclude the element(s) of the data sources 105 and/or the app server 125of FIG. 1.

The dynamic venue map 202 can connect to or be integrated with the EaaSplatform 230, such that the experiences created, delivered and managedusing the platform can include elements presented on the venue map 202,such as to visitors and to staff of the host. The SDK 250 anddevelopment application 252 may also generate and tweak a venue map 202,such as to allow developers to consider and integrate points ofinterest, routes, inventory locations, service locations, and otherfactors on the map when designing and delivering experiences. The venuemap 202 may integrate any of the information 140 discussed with respectto FIG. 1 and may also connect to or integrate with the systemsinfrastructure 204 of a location, such as to exchange data with elementsof the systems infrastructure 204 that are relevant to experiences, suchas sales and inventory data contained in point of sale (POS)infrastructure 212, to exchange location data with location-specific ornavigation infrastructure elements 208, such as beacons 216 and accesspoints 218 (e.g., WiFi hotspots and/or cell towers), and to coordinatewith content on media and signage infrastructure 214. The venue map 220may also connect to mobile devices 220, wearable devices 222 and theitineraries 228, so that map information can be presented on a visitor'sdevices, with appropriate itinerary information, messages, and the like,optionally presented in context using the map 202 as a presentationlayer. The itineraries 228 may be presented as lists, as a set ofdirections from the user's location to each consecutive POI/experience,or as a map that points out the user's location relative to eachconsecutive POI/experience (as in FIG. 4, FIG. 5, FIG. 6). In manyaspects of the present teachings, the dynamic venue map 202 can connectto the EaaS platform 230 through the physical world content managementsystem 238 and through use of the EaaS SDK 250, which may includevarious elements for creating, assembling, delivering and managingexperiences.

In aspects of the present teachings, the location systems infrastructure204 can include a venue inventory management system 206 and an indoornavigation infrastructure 208. Moreover, the location systemsinfrastructure 204 can make use of general networking infrastructure210. The location systems infrastructure 204 can include a POSinfrastructure 212, a media/display/signage infrastructure 214, beacons216, and access points 218. The venue inventory management systems 206can connect to the dynamic venue map 202, the indoor navigationinfrastructure 208 and general networking infrastructure 210. Thegeneral networking infrastructure 210 can connect to a POSinfrastructure 212, the media/display/signage infrastructure 214, thebeacons 216, the access points 218, and the like.

The mobile device 220 can include a mobile beacon 224. The mobile device220 can also connect to a wearable device 222 and can access theitineraries 228, such as to present an itinerary of a user or group onthe device. The mobile device 220 can also connect to the EaaS Platform230, the dynamic venue map 202, the location systems infrastructure 204and the EaaS SDK 250 to provide and receive data necessary to manage anexperience, to receive and redeem entitlements, to communicate aboutexperiences, to receive recommendations, to receive itineraries, and thelike. In additional aspects of the present teachings, the mobile device220 or wearable device 222 can connect to the location systemsinfrastructure 204, such as using the indoor navigation infrastructure208 or using other location capabilities, such as global positioningsystem (GPS) or cellular triangulation, so that the host can maintainprecise understanding of the user's location at all times. In aspects,the mobile device 220 of wearable device 222 can connect to the locationsystems infrastructure 204 through the venue inventory managementsystems 206, such as where the mobile device 220 or wearable device 222is used to order or purchase items, either at a point of sale or pointof interest, or remotely.

In various embodiments, the wearable device 222 can include or comprisea wearable beacon 226, such as to provide location information about theposition of the wearer of the wearable device 222, such as by detectingproximity to one or more points of interest (such as by detecting orinteracting with wireless infrastructure capabilities of the venue thatare known to be located at the points of interest via NFC, Bluetooth™,Bluetooth™ Low Energy (BTLE), WiFi, iBeacon, or other wireless signals,or other location methods, such as cellular triangulation, GPS, deadreckoning, user reporting of location, etc.). The wearable device 222can connect to or interact with the mobile device 220 and one or moreitineraries 228 (such as to receive information about current andupcoming itinerary items, such as the nature of the items, locations,times and routing information within the venue to the next or subsequentitem, as well as to receive information about entitlements, such astickets, that may be used, via the wearable device 222, in connectionwith items on the itinerary). The EaaS platform 230 can include orconnect to a reporting and analytics facility 232, which may takeinformation from various components of the EaaS platform 230, or otherelements that interact with the EaaS platform 230 and allow thegeneration of reports and analytic results on the data, such asinformation about what experiences have been recommended, whatexperiences have been undertaken by users, what entitlements have beenredeemed, what goods or services have been purchased, what profits havebeen made, and the like, in each case optionally presented by timeperiod, by location, by visitor, by group, by demographic factor, and bymany other variables. The analytics facility 232 may thus allow users,such as marketing staff of a host, to analyze the impact of any of thefactors captured in the various data sets used by the EaaS platform 230that may contribute to creation, recommendation, assembly, delivery, andcompletion of experiences, as measured by contribution of the factorsany of a wide variety of measures of performance (e.g., number ofvisits, duration of visits, frequency of visit, visitor satisfactionratings, profit per visitor, profit per time period, gross sales, netsales, gross profits, net profits, amounts paid by sponsors, rates paidby sponsors for sponsorship, and many other). Analytics may includevisualizations, such as heat maps, as well as presentations of resultsas an overlay on the dynamic venue map, such as showing whichattractions or points of interest are most popular, most profitable, orthe like. The analytics facility 232 may include capabilities forundertaking a wide range of analytic techniques, including A/B testingtechniques, correlation analysis (including use of similarity matrices,such as for collaborative filtering, as well as various knownstatistical techniques), analysis based on distributions (e.g., normaldistributions), probabilistic analysis (e.g., random walk and similaralgorithms), and many others. Output and results from the analyticsfacility 232 may be used to optimize recommendations, to suggest newexperiences, to improve performance of staff, to improve selection ofinventory, to optimize patterns of traffic within a venue, to improveprofits and yield, and for many other purposes.

Recommendations of experiences or points of interest (POI) may be madebased on user's location, on estimated time for the user to travel tothe point of interest, on wait times at the point of interest, on queuelengths at the point of interest, on popularity of the experience/POI,on the user never having been to the experience/POI before, on the userhaving been to the experience/POI more than a predetermined number oftimes already (indicating that the user likes the experience/POI), onexpected weather at the point of interest, on the experience or point ofinterest being related to something that the user likes according toprofile information concerning the user, on the experience or point ofinterest being unrelated to something that the user dislikes accordingto profile information concerning the user, on the type ofexperience/POI, on an amount of time since the was last at anexperience/POI of the same type exceeding a predetermined period oftime, on inventory at the POI, or some combination thereof.Recommendations of experiences and related points of interest may bemade based on such information concerning more than one user as well, sothat when a family is traveling together, for example, the likes anddislikes of each member of the family (and other information asdiscussed above concerning each member of the family) can be taken intoaccount to find optimal recommendations of experiences and points ofinterest.

A user's experience can importantly include experience with a particularvenue, or a particular type of venue. For example, the user profile canaccumulate, and reflect, the user's experience with a theme park, withtheme parks of a particular type, with a cruise ship, with visits tolocations within venues or around the world, and the like. Among otherthings, the user experience can keep track of what a user has doneduring past visits, including capturing positive and negative ratings,so that positive past experiences can be added to an itinerary orrecommended at appropriate times during a subsequent visit, or so thatsimilar experiences can be recommended or added to an itinerary at a newvenue. The user experience can also capture information about a currentvisit, such as indicating that a user has already experienced a certainattraction, event, service, or the like, so that the EaaS platform 230can steer the user to additional experiences or re-direct the user tofavorite experiences at appropriate times.

The user profile can also account for user interests, includinginterests in particular types of dining, foods or beverages, interestsin entertainment options (such as preferences in music, dancing, magicshows, animal shows, and many others), interests in attractions (such asthrill rides, water rides, arts, fireworks, fountains, historicalinformation, and many others), interests in particular characters,people or topics, and many others. These can be used, for example, toidentify relevant attractions that are either directly responsive to theuser's interests or that have been given positive ratings by similarusers. Interests can also be inferred, such as by identifying interestsof other users who have similar characteristics.

The EaaS platform 230 may include an assembly layer 234, and anexperience generator 236. The assembly layer 234 may be used to assemblean experience, such as by assembling various components that comprisethe experience, such as content (such as messaging and communications,recommendations, and the like, including multimedia content, brandedcontent, logos, and the like that may present aspects of theexperience), entitlements (such as tickets, reservations, coupons,discounts, passes (including line skipping passes) and the like, as wellas bar codes, QR codes, or other information needed to redeem anentitlement or undertake an experience), information about goods andservices (such as packages of foods and beverages that can be ready forthe visitor upon arrival), itinerary information (such as indicatingtime and place for the experience, wait time information, and the like),directional or navigation information, pricing information, and thelike. The assembly layer 234 may include user interfaces for a humanuser to assemble an experience, such as by authoring messages, selectingelements of an experience (including by menus, by drag-and-dropinterfaces that allow the user to pull items from libraries or database,and the like), setting parameters for the experience (such as pricingand discounts, timing factors (such as how long a discount isavailable), and the like. The assembly layer 234 may also includesemi-automated, or entirely machine-based assembly of experiences. Forexample, a machine learning capability of the assembly layer may use atraining set of assembled experiences as a basis for assembling(optionally under human supervision or with human confirmation)additional experiences that are similar to the ones created in thetraining set. Over time, the machine-based experience assemblycapability may use feedback (such as based on metrics indicatingsatisfaction by visitors with assembled experiences or indicatingprofitability or per-visitor yield for experiences) to improve thecapacity of the assembly layer 234 to assembly highly effectiveexperiences. The assembly layer 234 may also embody rules, such from arules engine 245, such as to mandate certain aspects of assembly ofexperiences or to preclude certain aspects of the assembly; for example,a rule might indicate that “no experience for a minor should includealcoholic beverages” or “all experiences between noon and 2:00 p.m.should include food and beverage recommendations.” Thus, through acombination of human creation, machine-automation and application ofrules, the assembly layer 234 allows the assembly of an experience. Theexperience generator 236 may take the experience assembled by theassembly layer 234 and generate a data structure reflecting the actualexperience, such as generating a message, with appropriate codes forredemption, entitlements, and the like, for delivery such as to thevisitor's mobile device or wearable device, and/or for delivery to apoint of sale, such as for use by staff of the host.

The EaaS platform 230 can also include or connect to a physical worldcontent management system 238, which may be used to manage variouscontent that is used to design, create, assemble, deliver, and recommendexperiences, such as multimedia content from various content libraries(e.g., branded content about products and services, attractions and thelike, video content about experiences, map content, content about pointsof interest (including location data, opening hours, mapping ofinfrastructure elements, such as beacons and displays, etc.)), as wellas information about visitors (such as user profile information asdiscussed in more detail below), information about other factors thatcan impact an experience (such as weather information), informationabout a venue (such as about available infrastructure, inventory, andthe like), information about the host, information about parameters ofexperiences (such as pricing, discounts, inventory levels, wait times,restrictions, prohibitions, and the like), and many other types ofcontent. The physical world content management system 238 is describedin more detail elsewhere in this disclosure. The EaaS platform 230 mayalso include a recommendation engine 240 for recommending experiences orpoints of interest (POI) or aspects of experiences, either directly to avisitor or to personnel of a host, such as to assist in assemblingexperiences or to assist staff in guiding visitors to favorableexperiences. The recommendation engine 240 is also described in moredetail elsewhere in this disclosure. The EaaS platform 230 may alsocreate, manage, and consume information from various userprofiles/identities 242, each of which may contain various identity,demographic, psychographic, geographic, historical, transactional,relational, social, personality, or other information that may indicatea user's likely preferences, relationships (such as membership in afamily social group, business group, or other group), or the like. Inthe context herein, the term “user” may refer to a venue attendee or auser of a particular mobile/wearable device 110 and/or front-end device135. The EaaS platform 230 can further include, connect to, or integratewith a context engine 243, which may be used to determine the context ofa visitor at a given time and place, such as taking into account thevisitor's identity, the time of day, the season, the weather, thepresence or proximity of various physical world elements (such as pointsof interest, displays, and infrastructure elements), the presence orproximity of other individuals (such as members of a family or socialgroup, or the like), the visitor's history (such as recent activities ortransactions, or longer-term activities that may indicate an interest ina type of activity), a visitor's current state (such as a level ofenergy or fatigue such as indicated by past activity (such asparticipation in physical exertion during hot weather)) or by tracking(such as by a wearable activity monitor) or a current mood (such asindicated by user survey), or by an indicator (such as from aphysiological monitor or facial recognition facility), or the like, orany of a wide variety of other elements that reflect the state orcontext of the visitor. The context engine 243 may include automatedelements, such as a machine learning facility, for automaticallydetermining, or predicting, a user's context, which may optionally betrained via a human-generated training set and optimized based onfeedback, such as indicators of the actual context of a visitor orindicators of particular factors used to determine that context. Forexample, visitors might provide feedback about energy levels, mood, orinterest that may be used to refine machine-learning models that infersuch factors based on other factors, such as time of day, weather, theconsumption foods, and the like. Output from the context engine 243 maybe provided to other aspects of the EaaS platform 230, such as theassembly layer, the experience generator, the SDK, the developmentapplication, and the like, so that experiences can be created that areappropriate for the context of a particular visitor or group.

The EaaS platform 230 may also include a sales activation engine 244,which may be used to assist personnel of the host in activating sales ofgoods and services that may be offered as part of or in conjunction withan experience. The sales activation engine 244 may take data from, forexample, an inventory system, so that a user of the sales activationengine 244 may be aware of what goods and services are in stock and atwhat levels, which goods and services need to be promoted (to maintainappropriate inventory levels), which ones are most complementary to eachother and to particular experiences or aspects of experiences, whichones are most profitable, and the like. A dashboard or interface of thesales activation engine 244 may allow personnel to determine what itemsshould be promoted given the current context of a visitor, including theidentity information, location, time of day, and other information andmay suggest assembly of an overall experience that is most likely topromote sales (and a high yield or profit). For example, a person whohas just waited in a long line on a hot day to participate in a thrillride may be offered a discounted favorite cold beverage (such as basedon past beverage purposes) at nearby point of interest, packaged with arecommendation for an experience that takes place there in an airconditioned environment. Embodiments of the sales activation engine 244may include automation, including machine learning, to automate therecommendation or assembly of items for sale, such as by using atraining set that is created by human personnel and subsequentlyoptimized based on feedback metrics, such as metrics on actual sales ofgoods and services, metrics on profitability, and the like. Rules fromthe rules engine 245 may be used to govern the use of the salesactivation engine 244, such as rules prohibiting certain types of salesactivation (e.g., “do not run more than 5 sales promotions per visitorper day” or “promote item X to all visitors today”). Output from thesales activation engine 244 may include direct messages to visitorspromoting items, as well as content for the assembly layer 234, such ascontent indicating what goods or services should be packaged or promotedwith a recommended experience.

As noted, the EaaS platform 230 may make use of rules, includingbusiness rules, in various components and methods described throughoutthis disclosure. Rules, such as business rules, may be developed,maintained and distributed using the rules engine 245. Rules may be usedto govern human-performed activities, such as ones used in variousinterfaces and dashboards to create, recommend, assemble, deliver andmanage experiences, as well as to govern automated activities, such assimilar ones performed based on machine learning.

The EaaS platform 230 can also connect to a beacon system 246, which maybe associated with a location database 248, such that locations ofbeacons 246 at various points of interest in a location can be known tothe EaaS platform 230, such as for use by humans, by machine-basedautomation or combination, as a basis for knowing where points ofinterest are and where other items (including detected items, suchmobile devices, wearable devices, and the like) are relative to thepoints of interest. The location database 248 may include locations ofbeacons, points of interest, inventory items, infrastructure elements(including communications infrastructure, media infrastructure, displayinfrastructure, facilities and the like), and the like. The locationdatabase 248 may include source information for use by various layers ofthe dynamic venue map as described in detail elsewhere in thisdisclosure.

The EaaS platform 230 may also include the EaaS SDK 250, which maycomprise a set of software tools, components, modules, libraries, andthe like for using the various aspects of the EaaS platform 230, such asfor taking outputs from and providing inputs to the context engine, therules engine, the location database, the assembly layer, the experiencegenerator, the recommendation engine, and other elements. This mayinclude various interfaces and similar elements for connecting to theEaaS platform 230 and its components, including APIs, connectors,gateways, buses, bridges, message brokers, hubs and the like. The SDKmay be used to create, assemble, deliver, and manage experiences, aswell as to manage and use aspects of the EaaS platform 230.

The EaaS platform 230 can connect to and use the itineraries 228, suchas to provide experiences to be included in an itinerary and to takeitinerary information as an input, such as to determine a next messageto provide to a user. Itineraries 228 are described in more detailelsewhere in this disclosure.

The EaaS platform 230 may interact with a mobile device 220 of a visitoror personnel of a host, such as for delivering messages and othercontent, delivering entitlements, redeeming entitlements, tracking userlocation, delivering sponsored content, and the like.

The EaaS platform 230 may use and integrate the dynamic venue map 202,such as presenting the map on a user device to show the venue, to guidevisitors to experiences, to show content about points of interest, toshow offers or promotions, to show sponsored content, or the like. Thedynamic venue map 202 may also be used as an interface for experiencedevelopers, such as using the SDK or the development application, wherestaff of a host may see where a visitor is located, see nearby points ofinterest, see inventory levels and the like, to help a staff memberdetermine an experience to recommend or provide information to a visitorabout an available experience. The dynamic venue map 202 may also beused for analytics, such as showing reports on various metrics that areassociated with points of interest at a location such as numbers ofvisits, sales levels, yields per visitor, inventory levels,profitability, and many others.

The EaaS platform 230 can also connect to the location systemsinfrastructure 204, such as to obtain current location data, such as thenumber of visitors detected in proximity to points of interest, and thelike. An analytics API 256 of the EaaS platform 230 may provide accessto various data from any of the components of the platform 230 forpurposes of analytics, including the analytics facility describedelsewhere in this disclosure and third party analytics facilities thatmay use the API to obtain information from the EaaS platform 230. TheEaaS platform 230 may include a user interface, such as a corporateviewer user interface (UI) 254, which may comprise a user interface bywhich staff, such as executive staff of a host, may see data aboutvarious aspects of the EaaS platform 230, including metrics onexperiences, visitors, visits, yields, and the like.

In embodiments, the analytics API 256 can connect to the EaaS platform230. The analytics API 256 can also connect to the EaaS Platform 230through the reporting and analytics facility 232. The corporate viewerUI 254 can connect to the EaaS platform 230. In further aspects, thecorporate viewer UI 254 can connect to the EaaS Platform 230 and makeuse of the reporting and analytics module 232.

Recommendations can also include coupons and promotions, sponsoredcontent, and the like. Available experiences can be delivered byoptional push notifications or can be made available to be pulled, suchas by interactions with a dynamic venue map 202, by searching (such asusing a mobile device), or the like. Recommendations can be sent byserver 125 to a staff member or to the guest. Recommendations can beintegrated into a personalized itinerary before being sent by server 125to a staff member or to the guest, the personalized itinerary optionallyincluding other experiences or POIs besides the experiences or POIsrecommended by the EaaS platform 230. Recommendations may also be basedon similarity or dissimilarity to other experiences or POIs in thepersonalized itinerary, such as experiences or POIs that were personallyselected by the user to whom the itinerary is personalized.

FIG. 3 illustrates information flow for real-time management ofexperiences and personalized itineraries. The information flow 300 ofFIG. 3 more specifically shows connections (each optionallybidirectional) between different types and/or sources of informationthat ultimately are used to produce a personalized itinerary 302/304 fora user 320. In relation to FIG. 1, any of the sources of information 140discussed with respect to FIG. 3 may be among any of data source(s) 105identified in FIG. 1 and/or may be stored at the app server(s) 125itself.

The EaaS platform 130, in the context of FIG. 3, can create and managean itinerary 302/304 for a user. The itinerary 302 can be for a fulljourney for a user within a venue, such as from a point of origin (e.g.,at home), to one or more locations/areas/venues (such as to a series ofcities on a trip, a series of islands or ports on a cruise as in FIG. 5or FIG. 6, or the like) and points of interest or sub-venues along theway (such as theme parks, ships, aircraft, ports, stores, malls,restaurants, bars, and many others). For each venue or sub-venue, anin-venue itinerary 304 can be generated, which in examples can be ahighly personalized personal itinerary 304 that is generated based onthe user profile 330 that may identify likes and dislikes and locationhistories of a user 320, as well as based on other information, such asfrom various third party data sources 340, which can include informationabout entitlements (such as tickets the user can have already obtainedto particular attractions or events, reservations the user can havealready made, and the like), information about expressed preferences,interests, or plans, information about climate and weather, and manyother items. Third party data sources 340 may include social mediaprofiles corresponding to users/attendees 320. Third party data sources340 may be part of the personal user profile 330, though they areillustrated separately in FIG. 3.

In examples, a live experience development application 352 can be usedto generate an in-venue personal itinerary 304 for the part of theitinerary 302 that is associated with a visit to a particular venue. Inaddition to using the user profile information 330 (which, as noted inthis disclosure, can account for relationships and connections with agroup, such that an itinerary for a user can be associated with, andmanaged in connection with, a larger group itinerary) and otherinformation about the full journey itinerary 302, the in-venue personalitinerary 304 can be dynamically created and account for other factors,such as current wait times and crowds (including adjusting the itinerary304 for flow control 308, so that users within a venue are spreadsmoothly across attractions, while still satisfying personal needs andgoals).

The itinerary 304 can also be repeatedly updated based on availableassets 312 (such as what attractions are open and have reasonable waittimes in the proximity of the user at a given time), the user's currentstate (such as whether the user expresses hunger, thirst, fatigue, orthe like, or such factors are inferred based on history), informationabout the user's group (such as locations and itineraries of the group),recommendations for the user (such as described in connection with therecommendation engine, including appropriate recommendations for theimmediate time and location as well as recommendations for laterexperiences. The itineraries 302 and 304 can be delivered and updated bythe messaging engine 310, such as by text or voice messages to theuser's mobile phone or wearable device, as well as by presentation ofinformation on the live, branded, dynamic venue map. For example, anitinerary can be shown on a map with the current location and currentlyrecommended item highlighted (such as in a color, with flashing symbols,or the like), and one or more alternative future recommendations shown,with routing information (including alternative available routes anditineraries) for the user.

The itinerary can show optional items as well as mandatory items (suchas the designated meetup location for a group). The EaaS platform 130,such as using the live experience development application 352 orautomatically, such as by machine learning, can constantly update theitinerary, such as accounting for changes. Changes can include the userhaving more time, because an attraction took less time than expected, orvice versa, or the user deciding to take a different route or dosomething different than was previously anticipated in the itinerary306. Changes can include changes in the inventory of tickets, goods,services, or the like near the user's location or at other locationsthat are later in the itinerary. Changes can include changes in waittimes. Changes can include changes in the user's state, such as becomingtired, hungry, thirsty, or bored. Changes can include changes initineraries for the user's group, changes in locations for members ofthe group, or the like. In each case, updated information can be used tosuggest a new itinerary that accounts for the current state of the userand the venue.

In many aspects, the EaaS platform 130 can track completion ofexperiences for an itinerary, such as by receiving location signals(such as an indication that a user's mobile phone or wearable device hasentered the proximity of a beacon that is positioned at a point ofinterest), by receiving evidence of redemption of entitlements (such asredemption of tickets, including electronic tickets, or redemption ofcredits, such as stored on a mobile device or wearable), and receivingevidence of purchases or consumption (such as indicated by transactiondata or other information from points of purchase located within avenue). Completed experiences can be recorded on the itinerary,prompting directions (such as messages or elements on a map, such asrouting information) for the next itinerary item, allowing theprogression through a series of locations, points of interest and thelike on the itinerary. As noted, changes in the venue, in the user'sstate, and other factors can lead to changes in the itinerary, which canbe managed automatically in the platform, can be managed by the user(such as by setting or approving items on the user's mobile phone), andcan be managed for the user by the experience provider, such as usingthe live experience development application 352.

In an example, a father and son are visiting a theme park. The liveexperience development application 352 is used to generate a fulljourney personal itinerary 302 for the father to follow during thevisit. The full journey personal itinerary 302 includes recommendationsbased on the personal user profiles 330 of the father and of the son.

For example, the personal user profiles 330 of the father and of the sonindicate the father-son relationship. The personal user profile 330 ofthe son indicates the son prefers to ride roller coasters, ride Ferriswheels and eat pizza. The personal user profile 330 of the fatherindicates the father has no ride preferences and prefers healthy eatingoptions.

The full journey personal itinerary 302 is also developed using datafrom third party data sources 340. For example, the father would like tominimize the cost of the trip and asked a question on a social networkabout how to minimize costs during a trip to a theme park. This questionis used to signal to the live experience development application 352 toinclude special deals and offers in the full journey personal itinerary302. Such information may alternately be included in the father's userprofile.

When in a group, all of this information concerning both the father andthe son may be used to generate recommendations for experiences and/orpoints of interest (POIs). For example, the son's preference for pizzaand the father's preference for healthy eating options may result in arecommendation for a restaurant that provides both pizza and healthyeating options. The son's preference for roller coasters and ferriswheels combined with the father's preference for minimizing costs of thetrip may result in a recommendation for the lowest-cost roller coasteror ferris wheel rides. This may be combined with locations of the fatherand son so as to recommend POIs that are near both the father and theson or along a route that they are known to be using based on other POIs(such as self-selected POIs) in their group itinerary or separaterespective itineraries.

FIG. 4 illustrates a dynamic live venue map identifying a personalizeditinerary in a theme park venue. The dynamic live venue map 400 of FIG.4 may be one implementation of a dynamic venue map 202 as discussed withrespect to FIG. 2 and/or a personalized itinerary 302/304 as discussedwith respect to FIG. 3.

Available assets 312 in the context of FIG. 4 indicate there are tworoller coasters (roller coaster A 402 and roller coaster B 404), aFerris wheel 406, a healthy eating restaurant 408, a theme park entrance412, and a parking lot 410 available at the theme park. The user'slocation 450 is marked on the map, with a solid line indicating that theuser has traveled from the parking lot 410 to the theme park entrance412 and is now standing between the theme park entrance 412 and theFerris wheel 406. The Ferris wheel 406, the healthy eating restaurant408 (optionally if the user is hungry as marked using a dashed box), andthe Roller coaster A 402 are included on the full journey personalitinerary 302 of FIG. 4. Available inventory 314 indicates theingredients for salads at a healthy eating restaurant 408 are nearingthe end of their shelf life, and this inventory information can be acomponent in recommending or not recommending the healthy eatingrestaurant 408. The healthy eating restaurant 408 is also included onthe full journey personal itinerary 302 of FIG. 4 for at least thisreason.

Presentation layer development can include the use of a dynamic/livevenue map 400. The dynamic/live venue map 400 can include point ofinterest (POI) locations 404, 402, 406, 408, 410, 412, which can bedynamically updated based on changes occurring within a venue or managedlocation. In many aspects, wait time can be an example of point ofinterest data or metadata associated with a location or point on thedynamic map. By way of this example, the point of interest data or mappoint metadata for one or more destinations can be pulled and updatedamong the users. In these examples, the point of interest data or mappoint metadata can include menu data for the restaurant, wait times formany points of interest at a managed location, or the like.

The personalized itinerary map of FIG. 4 may include recommendations forand based on two users, to relate FIG. 4 back to the father/son examplediscussed with respect to FIG. 3. The full journey personal itinerary302 is sent prior to the visit via the messaging engine 310 to thevisitor device/wearable 110 of the father, which is acting as afront-end device 135 in the context of FIG. 1. The full journey personalitinerary 302 can stretch back before arrival at the venue (the themepark) to also include directions to the theme park from the father's andson's home, as well as parking information. Parking information isupdated based on the available inventory 314 of parking. This guides thefather and son to an available parking lot 410, minimizing time theyhave to spend searching for an available parking space.

The EaaS platform 130 detects when the father and son enter the themepark, by detecting that a beacon on the mobile phone of the father hasentered the boundaries of the theme park. An in-venue personal itinerary304 is sent to the mobile phone of the father when the EaaS platform 130detects the father and son have entered the theme park.

The in-venue personal itinerary 304 includes a dynamic/live venue map400. In this example, roller coaster A 402, roller coaster B 404, Ferriswheel 406 and healthy eating restaurant 408 are displayed as POIlocations on the dynamic/live venue map 400.

The in-venue personal itinerary 304 suggests that the father and sonride roller coaster A 402 first, since roller coaster A is located closeto the theme park entrance 412. Because it is before noon, the in-venuepersonal itinerary 304 suggests the father and son ride roller coaster B404 second, before having lunch.

After riding roller coaster A 402, the father indicates in his userstate (which may be part of the user profile information) that thefather and son are hungry. Alternately, the EaaS platform may deducethat the father and son are likely hungry based on a time since theywere last at a food establishment exceeding a predetermined amount oftime (e.g, 3 hours). Based on this indication, a healthy eatingrestaurant 408 located in close proximity to the exit of Ferris Wheel406 is displayed as a dynamic map location 408 on dynamic/live venue map400.

The healthy eating restaurant 408 also serves salads. Because theingredients used to make salads are near the end of their shelf life, abuy-one-get-one-free salad offer is generated. Healthy eating restaurant408 is then highlighted on the dynamic/live venue map 400, indicating adeal on salads is available. The father chooses the healthy eatingrestaurant 408 for him and his son to have lunch and orders salads forboth of them, redeeming the buy-one-get-one-free salad offer.

In one example, the father and son may have had plans to ride rollercoaster B 404 after lunch. The EaaS platform 130 used wait time data orqueue length data from information 140 (as discussed with respect toFIG. 1) to detect that wait time at the Roller Coaster A 402 was short(or zero), while wait time at roller coaster B 404 was significant(e.g., exceeding a predetermined duration of time), indicating a shorterline at the Roller Coaster A 402 than at the Roller Coaster B 404, asthe father and son were finishing lunch. As the father and son werefinishing lunch, the dynamic map location of the Roller Coaster A 402 onthe dynamic/live venue map 400 turned green, indicating there was noline at the Roller Coaster A 402. Since there was no line at the Ferriswheel 406, the father and son decided to ride the Roller Coaster A 402after lunch, rather than ride roller coaster B 404.

With reference to FIG. 2, the present teachings generally include realtime management of highly personalized experiences of customers, theirfamilies, traveling companions or the like. The real time management ofhighly personalized experiences at managed locations can be integratedinto many of the operations and offerings at the managed locations. Theoperations and offerings at the managed locations can include events andentertainment offerings, but also includes fare offered by the location,and transport to and from the managed locations. With regard totransport to and from the managed locations, the real time management ofhighly personalized experiences of customers can coordinate the managedlocation to guide patrons to proper surface parking, garages, parkingtrams, or other forms of transportation that can be used.

The real time management of highly personalized experiences of customerscan connect to the computing devices of the customers and their familymembers, as well as computing devices of the host and its personnel,including staff at the venue and personal located remote from the venue.The computing devices can include phones, tablets, watches, wearabledevices (including ones dedicated to use at the venue), augmentedreality or virtual reality glasses, as well as laptop and desktopcomputers, servers, and the like. In connecting to the computing devicesof customers, cellular network and cloud network facilities can beemployed to ensure interconnection. The real time management of highlypersonalized experiences of customers can also connect with sponsors(such as advertisers) so as to be able to provide sponsored content tothe customers at the managed locations. The sponsored content can berelated in real-time to what is occurring with the user and/or thefamily of the user, their itinerary, the time of day and many factorsrelating to placement of sponsored content.

FIG. 5 illustrates a recommended itinerary map interface for a singleuser. The recommended itinerary map interface 500 of FIG. 5 may be oneimplementation of a dynamic venue map 202 as discussed with respect toFIG. 2 and/or a personalized itinerary 302/304 as discussed with respectto FIG. 3. In particular, the recommended itinerary map interface 500 ofFIG. 5 maps a personalized itinerary including recommended POIs anduser-selected POIs for a user “Matt” within a map 590 of a venueselected to be Eastern North America.

The recommended itinerary map interface 500 of FIG. 5 identifies a pastPOI 505 as the port of New York, which the user “Matt” was atpreviously. A first recommended POI 510 is provided by the EaaS platform230 as “Cruiseline Burger Grill.” The recommended POI 510 is recommendedbased on its location being along an existing route (from the user'scurrent location 530 to selected POI 515) and based on similarity tosomething that the user “Matt” likes according to his user profile(“Ike's Sadwiches”). A second POI 515 along the personalized itineraryis user-selected—Flamenco Beach in Culebra. A third POI 520 along thepersonalized itinerary is recommended by the EaaS platform 230 as “MiamiSurf Lessons” based on its location being along an existing route (fromthe user-selected POI 515 back to the port of New York 505) and based onsimilarity to the user-selected POI 515 (Flamenco Beach in Culebra) inthat both POIs are related to surfing.

The resulting map interface 500 illustrates a journey line 580representing a path connecting the POIs 505, 510, 515, 520, and back to505, the journey line 580 also connecting the current location 530 ofthe user. In some cases, a path 580 may be somewhat pre-set, as in apre-set cruise, in which case recommended POIs may be recommendedbecause they are along that path 580 and one or more additional reasons,such as similarity to “likes” of the user or dissimilarity to “dislikes”of the user or any of the other reasons identified above.

FIG. 6 illustrates a recommended itinerary map interface for two users.The recommended itinerary map interface 600 of FIG. 6 may be oneimplementation of a dynamic venue map 202 as discussed with respect toFIG. 2 and/or a personalized itinerary 302/304 as discussed with respectto FIG. 3. In particular, the recommended itinerary map interface 600 ofFIG. 6 maps a personalized itinerary including recommended POIs anduser-selected POIs for two users “Matt” and “Sam” within a map 690 of avenue selected to be Eastern North America.

The recommended itinerary map interface 600 of FIG. 6 identifies a pastPOI 605 as the port of New York, which the users “Matt” and “Sam” wereboth at previously. A first recommended POI 610 is provided by the EaaSplatform 230 as “Cruiseline Burger Grill.” The recommended POI 610 isrecommended based on its location being along an existing route (fromthe current location of both users 630 to selected POI 615) and based ondissimilarity to something that both users (“Matt” and “Sam”) dislikeaccording to their respective user profiles (sushi). A second POI 615along the personalized itinerary is user-selected—Flamenco Beach inCulebra. A third POI 620 along the personalized itinerary is recommendedby the EaaS platform 230 as “Miami Surf Lessons” based on its locationbeing along an existing route (from the user-selected POI 615 back tothe port of New York 605) and based on similarity to something that bothusers (“Matt” and “Sam”) like according to their respective userprofiles (sports).

While the recommended itinerary map interfaces 400, 500, 600, and 1000of FIG. 4, FIG. 5, FIG. 6, and FIG. 10 respectively, are all maps, itshould be understood that a personalized itinerary can take the form ofa list of POIs, either in order of when they should be visited or in adifferent order.

The resulting map interface 600 illustrates a journey line 680representing a path connecting the POIs 605, 610, 615, 620, and back to605, the journey line 680 also connecting the current location 630 ofthe users. In some cases, a path 680 may be somewhat pre-set, as in apre-set cruise, in which case recommended POIs may be recommendedbecause they are along that path 680 and one or more additional reasons,such as similarity to “likes” of one or more of the users ordissimilarity to “dislikes” of one or more of the users or any of theother reasons identified above.

FIG. 7 illustrates delivery of itinerary personalization to users.

With reference to FIG. 7, the present teachings generally include realtime management of highly personalized experiences of customers, theirfamilies, traveling companions or the like. The real time management ofhighly personalized experiences at managed locations can be integratedinto many of the operations and offerings at the managed locations. Theoperations and offerings at the managed locations can include events andentertainment offerings, but also includes fare offered by the location,and transport to and from the managed locations. With regard totransport to and from the managed locations, the real time management ofhighly personalized experiences of customers can coordinate the managedlocation to guide patrons to proper surface parking, garages, parkingtrams, or other forms of transportation that can be used.

The real time management of highly personalized experiences of customerscan connect to the computing devices of the customers and their familymembers, as well as computing devices of the host and its personnel,including staff at the venue and personal located remote from the venue.The computing devices can include phones, tablets, watches, wearabledevices (including ones dedicated to use at the venue), augmentedreality or virtual reality glasses, as well as laptop and desktopcomputers, servers, and the like. In connecting to the computing devicesof customers, cellular network and cloud network facilities can beemployed to ensure interconnection. The real time management of highlypersonalized experiences of customers can also connect with sponsors(such as advertisers) so as to be able to provide sponsored content tothe customers at the managed locations. The sponsored content can berelated in real-time to what is occurring with the user and/or thefamily of the user, their itinerary, the time of day and many factorsrelating to placement of sponsored content.

In short, the personalized itineraries 302/304 or maps 202 discussedherein may include recommended POIs based on any of the informationdiscussed in FIG. 7, including for example information concerningtransportation method, availability of rides using differenttransportation methods, scheduled events, campus entertainment, food andvending services inventory, location, wait times, parking locations andavailability, open parking space information, coordination with venuetransport, proximity to event location, vehicle and/or user and/ormobile device location, local relevant traffic information, advertisingcontent directed to customer or activity or event, sponsored POIs.

FIG. 8 illustrates an exemplary computing system 800 that may be used toimplement some aspects of the subject technology. For example, any ofthe computing devices, computing systems, network devices, networksystems, servers, and/or arrangements of circuitry described herein mayinclude at least one computing system 800, or may include at least onecomponent of the computer system 800 identified in FIG. 8. The computingsystem 800 of FIG. 8 includes one or more processors 810 and memory 820.Each of the processor(s) 810 may refer to one or more processors,controllers, microcontrollers, central processing units (CPUs), graphicsprocessing units (GPUs), arithmetic logic units (ALUs), acceleratedprocessing units (APUs), digital signal processors (DSPs), applicationspecific integrated circuits (ASICs), field-programmable gate arrays(FPGAs), or combinations thereof. Each of the processor(s) 810 mayinclude one or more cores, either integrated onto a single chip orspread across multiple chips connected or coupled together. Memory 820stores, in part, instructions and data for execution by processor 810.Memory 820 can store the executable code when in operation. The system800 of FIG. 8 further includes a mass storage device 830, portablestorage medium drive(s) 840, output devices 850, user input devices 860,a graphics display 870, and peripheral devices 880.

The components shown in FIG. 8 are depicted as being connected via asingle bus 890. However, the components may be connected through one ormore data transport means. For example, processor unit 810 and memory820 may be connected via a local microprocessor bus, and the massstorage device 830, peripheral device(s) 880, portable storage device840, and display system 870 may be connected via one or moreinput/output (I/O) buses.

Mass storage device 830, which may be implemented with a magnetic diskdrive or an optical disk drive, is a non-volatile storage device forstoring data and instructions for use by processor unit 810. Massstorage device 830 can store the system software for implementing someaspects of the subject technology for purposes of loading that softwareinto memory 820.

Portable storage device 840 operates in conjunction with a portablenon-volatile storage medium, such as a floppy disk, compact disk orDigital video disc, to input and output data and code to and from thecomputer system 800 of FIG. 8. The system software for implementingaspects of the subject technology may be stored on such a portablemedium and input to the computer system 800 via the portable storagedevice 840.

The memory 820, mass storage device 830, or portable storage 840 may insome cases store sensitive information, such as transaction information,health information, or cryptographic keys, and may in some cases encryptor decrypt such information with the aid of the processor 810. Thememory 820, mass storage device 830, or portable storage 840 may in somecases store, at least in part, instructions, executable code, or otherdata for execution or processing by the processor 810.

Output devices 850 may include, for example, communication circuitry foroutputting data through wired or wireless means, display circuitry fordisplaying data via a display screen, audio circuitry for outputtingaudio via headphones or a speaker, printer circuitry for printing datavia a printer, or some combination thereof. The display screen may beany type of display discussed with respect to the display system 870.The printer may be inkjet, laserjet, thermal, or some combinationthereof. In some cases, the output device circuitry 850 may allow fortransmission of data over an audio jack/plug, a microphone jack/plug, auniversal serial bus (USB) port/plug, an Apple® Lightning® port/plug, anEthernet port/plug, a fiber optic port/plug, a proprietary wiredport/plug, a BLUETOOTH® wireless signal transfer, a BLUETOOTH® lowenergy (BLE) wireless signal transfer, a radio-frequency identification(RFID) wireless signal transfer, near-field communications (NFC)wireless signal transfer, 802.11 Wi-Fi wireless signal transfer,cellular data network wireless signal transfer, a radio wave signaltransfer, a microwave signal transfer, an infrared signal transfer, avisible light signal transfer, an ultraviolet signal transfer, awireless signal transfer along the electromagnetic spectrum, or somecombination thereof. Output devices 850 may include any ports, plugs,antennae, wired or wireless transmitters, wired or wirelesstransceivers, or any other components necessary for or usable toimplement the communication types listed above, such as cellularSubscriber Identity Module (SIM) cards.

Input devices 860 may include circuitry providing a portion of a userinterface. Input devices 860 may include an alpha-numeric keypad, suchas a keyboard, for inputting alpha-numeric and other information, or apointing device, such as a mouse, a trackball, stylus, or cursordirection keys. Input devices 860 may include touch-sensitive surfacesas well, either integrated with a display as in a touchscreen, orseparate from a display as in a trackpad. Touch-sensitive surfaces mayin some cases detect localized variable pressure or force detection. Insome cases, the input device circuitry may allow for receipt of dataover an audio jack, a microphone jack, a universal serial bus (USB)port/plug, an Apple® Lightning® port/plug, an Ethernet port/plug, afiber optic port/plug, a proprietary wired port/plug, a BLUETOOTH®wireless signal transfer, a BLUETOOTH® low energy (BLE) wireless signaltransfer, a radio-frequency identification (RFID) wireless signaltransfer, near-field communications (NFC) wireless signal transfer,802.11 Wi-Fi wireless signal transfer, cellular data network wirelesssignal transfer, a radio wave signal transfer, a microwave signaltransfer, an infrared signal transfer, a visible light signal transfer,an ultraviolet signal transfer, a wireless signal transfer along theelectromagnetic spectrum, or some combination thereof. Input devices 860may include any ports, plugs, antennae, wired or wireless receivers,wired or wireless transceivers, or any other components necessary for orusable to implement the communication types listed above, such ascellular SIM cards.

Display system 870 may include a liquid crystal display (LCD), a plasmadisplay, an organic light-emitting diode (OLED) display, an electronicink or “e-paper” display, a projector-based display, a holographicdisplay, or another suitable display device. Display system 870 receivestextual and graphical information, and processes the information foroutput to the display device. The display system 870 may includemultiple-touch touchscreen input capabilities, such as capacitive touchdetection, resistive touch detection, surface acoustic wave touchdetection, or infrared touch detection. Such touchscreen inputcapabilities may or may not allow for variable pressure or forcedetection.

Peripherals 880 may include any type of computer support device to addadditional functionality to the computer system. For example, peripheraldevice(s) 880 may include a modem, a router, an antenna, a printer, abar code scanner, a quick-response (“QR”) code scanner, a document/imagescanner, a visible light camera, a thermal/infrared camera, anultraviolet-sensitive camera, a night vision camera, a light sensor, abattery, a power source, or some combination thereof.

The components contained in the computer system 800 of FIG. 8 are thosetypically found in computer systems that may be suitable for use withsome aspects of the subject technology and are intended to represent abroad category of such computer components that are well known in theart. Thus, the computer system 800 of FIG. 8 can be a personal computer,a hand held computing device, a telephone (“smart” or otherwise), amobile computing device, a workstation, a server (on a server rack orotherwise), a minicomputer, a mainframe computer, a tablet computingdevice, a wearable device (such as a watch, a ring, a pair of glasses,or another type of jewelry/clothing/accessory), a video game console(portable or otherwise), an e-book reader, a media player device(portable or otherwise), a vehicle-based computer, some combinationthereof, or any other computing device. The computer system 800 may insome cases be a virtual computer system executed by another computersystem. The computer can also include different bus configurations,networked platforms, multi-processor platforms, etc. Various operatingsystems can be used including Unix, Linux, Windows, Macintosh OS, PalmOS, Android, iOS, and other suitable operating systems.

In some cases, the computer system 800 may be part of a multi-computersystem that uses multiple computer systems 800, each for one or morespecific tasks or purposes. For example, the multi-computer system mayinclude multiple computer systems 800 communicatively coupled togethervia at least one of a personal area network (PAN), a local area network(LAN), a wireless local area network (WLAN), a municipal area network(MAN), a wide area network (WAN), or some combination thereof. Themulti-computer system may further include multiple computer systems 800from different networks communicatively coupled together via theinternet (also known as a “distributed” system).

Some aspects of the subject technology may be implemented in anapplication that may be operable using a variety of devices.Non-transitory computer-readable storage media refer to any medium ormedia that participate in providing instructions to a central processingunit (CPU) for execution and that may be used in the memory 820, themass storage 830, the portable storage 840, or some combination thereof.Such media can take many forms, including, but not limited to,non-volatile and volatile media such as optical or magnetic disks anddynamic memory, respectively. Some forms of non-transitorycomputer-readable media include, for example, a floppy disk, a flexibledisk, a hard disk, magnetic tape, a magnetic strip/stripe, any othermagnetic storage medium, flash memory, memristor memory, any othersolid-state memory, a compact disc read only memory (CD-ROM) opticaldisc, a rewritable compact disc (CD) optical disc, digital video disk(DVD) optical disc, a blu-ray disc (BDD) optical disc, a holographicoptical disk, another optical medium, a secure digital (SD) card, amicro secure digital (microSD) card, a Memory Stick® card, a smartcardchip, a Europay®/Mastercard®/Visa® (EMV) chip, a subscriber identitymodule (SIM) card, a mini/micro/nano/pico SIM card, another integratedcircuit (IC) chip/card, random access memory (RAM), static RAM (SRAM),dynamic RAM (DRAM), read-only memory (ROM), programmable read-onlymemory (PROM), erasable programmable read-only memory (EPROM),electrically erasable programmable read-only memory (EEPROM), flashEPROM (FLASHEPROM), cache memory (L1/L2/L3/L4/L5/L8), resistiverandom-access memory (RRAM/ReRAM), phase change memory (PCM), spintransfer torque RAM (STT-RAM), another memory chip or cartridge, or acombination thereof.

Various forms of transmission media may be involved in carrying one ormore sequences of one or more instructions to a processor 810 forexecution. A bus 890 carries the data to system RAM or another memory820, from which a processor 810 retrieves and executes the instructions.The instructions received by system RAM or another memory 820 canoptionally be stored on a fixed disk (mass storage device 830/portablestorage 840) either before or after execution by processor 810. Variousforms of storage may likewise be implemented as well as the necessarynetwork interfaces and network topologies to implement the same.

FIG. 9 illustrates identification of similar users based on sharedtraits. In the context of FIG. 9, FIG. 10, and otherwise herein, itshould be understood that the term “user” may refer to venue attendeesor venue guests, and the term “user profile” may be referred to as a“venue attendee profile” or a “venue guest profile.”

Three user profiles are illustrated in FIG. 9—a first user profile 905corresponding to a first venue attendee (“Adam Anderson”) with anincluded photo 910 of the first venue attendee, a second user profile925 corresponding to a second venue attendee (“Betty Brown”) with anincluded photo 930 of the second venue attendee, and a third userprofile 945 corresponding to a third venue attendee (“Charlene Cooper”)with an included photo 950 of the third venue attendee.

Each user profile lists a number of traits about the corresponding venueattendee along with the photo 910/930/950. In FIG. 9, these each userprofile lists the same traits about every venue attendee, but in othersituations, different user profiles may list different types of traits,with some traits missing from certain user profiles and some additionaltraits listed in certain user profiles. In FIG. 9, the traits listedinclude first name, last name, age, age group, gender, hometown,occupation, recent location, the last time that the venue attendee hasvisited the venue, the venue attendee's most frequently visited point ofinterest (POI) in the venue area, the venue attendee's last (mostrecently) visited point of interest (POI) in the venue area, the venueattendee's most highly-rated point of interest (POI) in the venue area,the venue attendee's most recent purchase at a point of interest (POI)in the venue area, a diet that the venue attendee is following, anyallergies that the venue attendee has, food that the venue attendeelikes or prefers, food that the venue attendee dislikes or cannot eat,subjects that the venue attendee likes or prefers, and subjects that thevenue attendee dislikes.

The app server(s) 125 or other computing devices 800 implementing therecommendation experience as a service (EaaS) platform 230 may retrievethe various data in each user profile—that is, the photos 910/930/950and the various listed traits corresponding to each venue attendee—fromvarious data sources, such as databases or other data structures in alocal memory of the EaaS platform 230, databases or other datastructures stored by network servers accessible via local area network(LAN) by the EaaS platform 230, databases or other data structuresstored by remote servers accessible via the internet by the EaaSplatform 230, or combinations thereof. These databases or other datastructures may be associated with the venue itself, and at least some ofthe data included therein may for example be collected upon entry intothe venue area and/or upon entry to certain POIs within the venue area.These databases or other data structures may be shared the EaaS platform230 actively by the user or may be otherwise collected, retrieved,scraped, and/or parsed by the EaaS platform 230. These databases orother data structures may be associated with social media networks, suchas Facebook®, LinkedIn®, Instagram®, Snapchat®, Youtube®, Pinterest®, orsimilar social media networks. These databases or other data structuresmay be associated with online dating platforms. These databases or otherdata structures may be associated with professional websites or jobhunting websites. Different user profiles may be gathered from the samedata sources or from different data sources. For example, in FIG. 9,user profile 905 is listed as comprising data from a database 915 and adatabase 920, user profile 925 is listed as comprising data from adatabase 935 and a database 940, and user profile 945 is listed ascomprising data from the database 915 and a database 955.

The app server(s) 125 or other computing devices 800 implementing theexperience as a service (EaaS) platform 230 can find similarities ordissimilarities between different venue attendees for use later withrecommending POIs or personalizing itineraries as illustrated in anddiscussed with respect to FIG. 10. Finding of similar or dissimilarvenue attendees is based on finding one or more shared traits that arecommon to two or more user profiles, such as the user profiles 905, 925,and 945 shown in FIG. 9.

For example, age group is a shared trait 960 common to user profile 905and user profile 925, as both are in the age group “young adults (ages18-35).” Most frequently visited point of interest (POI) in the venuearea is another shared trait 965 common to user profile 905 and userprofile 925, as both are listed as the POI “Retro Diner,” which userAdam Anderson of user profile 905 has visited 9 times and given a 3/5rating, and which user Betty Brown of user profile 25 has visited 4times and provided no known review or rating. Allergies is anothershared trait 970 common to user profile 905 and user profile 925, asboth users are listed as allergic to peanuts. Food likes/preferences isanother shared trait 975 common to user profile 905 and user profile925, as both users are listed as enjoying/liking/preferring tacos. Thus,user profile 905 and user profile 925 as shown in FIG. 9 have at leastfour shared traits in common.

Gender is a shared trait 980 common to user profile 925 and user profile945, as both users are female. Diet is another shared trait 985 commonto user profile 925 and user profile 945, as one user is vegetarian andthe other user is vegan—which the EaaS platform 230 may recognize assimilar enough though they are not identical. Subject likes/preferencesis another shared trait 990 common to user profile 925 and user profile945, as they both enjoy/like/prefer chemistry. Thus, user profile 925and user profile 945 as shown in FIG. 9 have at least three sharedtraits in common.

In situations where the EaaS platform 230 find multiple users to besimilar to a particular user, the EaaS platform 230 may rank thosemultiple users based on how many shared traits are found in commonbetween the user profiles corresponding to those users. For example,because user profile 905 and user profile 925 as shown in FIG. 9 havefour shared traits in common while user profile 925 and user profile 945as shown in FIG. 9 have only three shared traits in common, user BettyBrown associated with user profile 925 may be identified by the EaaSplatform 230 as being more similar to user Adam Anderson associated withuser profile 905 than to user Charlene Cooper associated with userprofile 945.

Once the experience as a service (EaaS) platform 230 identifies that afirst user is similar to a second user, it may generate a recommendationof a particular POI for the first user, and/or personalized itineraryincluding a recommendation for the particular POI for the first user,based on one or more indicator(s) of positivity associated with theparticular POI and corresponding to the second user.

An indicator of positivity associated with a POI and corresponding to auser may be, for example, one or more ratings exceeding a predeterminedthreshold rating, one or more reviews that include phrases associatedwith positivity, selection by the user of the POI, recommendation of thePOI to the user by the EaaS platform 230, or combinations thereof.Phrases associated with positivity in reviews may include phrases orphrases like “good,” “great,” “delicious,” “amazing,” “phenomenal,”“incredible,” translations of those phrases into other languages, andthe like.

In some cases—especially those in which a similar user mostly orexclusively expresses indicators of negativity about various POIs—anindicator of positivity may be simply the lack of an indicator ofnegativity. Indicators of negativity may include, for example, one ormore ratings below a predetermined threshold rating, one or more reviewsthat include phrases associated with negativity, avoidance by the userof the POI, or combinations thereof. Phrases associated with negativityin reviews may include phrases like “bad,” “terrible,” “awful,”“horrible,” “made me sick,” “made us sick,” “disgusting,” “incredible,”swear words, translations of those phrases into other languages, and thelike. Where a review includes both phrases associated with positivityand negativity, a sum can be generated of the “value” of all of thephrases associated with positivity and negativity, where phrasesassociated with positivity are given a positive value (such as 1) andphrases associated with negativity are given a negative value (such as−1). If the sum is positive, the review can be treated as positive, andif the sum is negative, the review can be treated as negative.

It should be understood that the terms “user,” “venue attendee” and“venue” guest can be used interchangeably at least with respect to FIG.9 and FIG. 10, and that “venue attendee” or “venue guest” can refer toformer venue attendees or venue guests—that is, persons who previouslyvisited the venue area but are no longer located in the venue area. Thatis, the EaaS platform 230 can determine that a venue attendee that iscurrently at the venue is similar to a former venue attendee thatvisited the venue over a year ago, and generate a recommendation for aparticular POI and/or personalized itinerary including a recommendationfor the particular POI based on indicator(s) of positivity associatedwith the particular POI and corresponding to that former venue attendee.

In a “tie” situation where a particular user is equally similar tomultiple similar users, the EaaS platform 230 can pick one of thosemultiple similar users at random and select the recommended POI based onan indicator of positivity associated with the POI that is then selectedto be the recommended POI corresponding to that one picked similar user.Alternately, the EaaS platform 230 can use multiple of those multiplesimilar users by finding a POI for which multiple similar users all haveindicators of positivity about the same POI, and selecting that POI tothe recommended POI for the user to which they are similar.

Ranking can be made more complex than a simple count of shared traits incommon between two profiles, however, to provide greater specificity andto limit “tie” situations. Certain shared traits can be weighted via amultiplier to be counted as more or less important than other sharedtraits. For example, shared allergies can be weighted to be moreimportant than shared subject matter preferences, for example by havingshared allergies count as 1.5 shared traits while shared subject matterpreferences count as 1 shared trait or even 0.9 shared trait. Similarly,age group can be weighted to be more important than age or vice versa,and occupation can be weighted to be more important than hometown, orany other combination of weighting.

While not illustrated explicitly in FIG. 9, the EaaS platform 230 canalso be used to find dissimilarities or explicit mismatches betweenusers. These can be found, for example, where a “like” or “preference”for one user is identified as a “dislike” or even an allergy for anotheruser. For example, a dissimilarity or mismatch would be found betweenuser profile 905 and user profile 925 because user profile 905 includes“pirates” in the trait category “subject likes,” while user profile 925includes “pirates” in the trait category “subject dislikes.” Similarly,a dissimilarity or mismatch would be found between user profile 945 andboth user profiles 905 and 925 because user profile 945 includes“peanuts” in the trait category “food likes,” while user profiles 905and 925 identify “peanuts” under “allergies.” Such dissimilarities ormismatches can be weighted by a multiplier as discussed above withrespect to similarities, and can be used to affect similarity rankingsby subtracting 1 shared trait (or a weighted value, such as 1.5 or 0.5)from the ranking.

Sometimes, the EaaS platform 230 may generate requirements based oncertain traits that are determined to be extremely important. Forexample, the “allergies” trait is very important in that if a user eatsor is otherwise exposed to something that they are allergic to, therecould be severe medical consequences for that user. Therefore, EaaSplatform 230 may generate a requirement that any recommended POIs besafe for someone with that allergy and/or that any user deemed to besimilar must be similar at least in terms of allergies.

FIG. 10 illustrates a recommended itinerary map interface for two usersin which certain recommendations are generated based on similarities toother users.

The recommended itinerary map interface 1000 of FIG. 10 may be oneimplementation of a dynamic venue map 202 as discussed with respect toFIG. 2 and/or a personalized itinerary 302/304 as discussed with respectto FIG. 3. In particular, the recommended itinerary map interface 1000of FIG. 10 maps a personalized itinerary including recommended POIs anduser-selected POIs for two users “Matt” and “Sam” within a map 1090 of avenue selected to be Eastern North America. The recommended itinerarymap interface 1000 of FIG. 10, in this way, is similar to therecommended itinerary map interface 600 of FIG. 6, though itincorporates recommended POIs based on similar users as discussed withrespect to FIG. 9.

The recommended itinerary map interface 1000 of FIG. 10 identifies apast POI 1005 as the port of New York, which the users “Matt” and “Sam”were both at previously. A first recommended POI 1010 is provided by theEaaS platform 230 as “Cruiseline Burger Grill.” The recommended POI 1010is recommended based on its location being along an existing or plannedroute (from the current location of both users 1030 to selected POI1015) and based on the POI 1010 (“Cruiseline Burger Grill”) having highratings (an indicator of positivity) from Betty, a user that the EaaSplatform 230 determined to have similar food preferences (a sharedtrait) to both Matt and Sam. While in this example, Betty was identifiedas similar to both Matt and Sam, it should be understood that the samePOI may have been recommended if Betty was identified as only similar toMatt or only similar to Sam.

A second POI 1015 along the personalized itinerary is user-selected bySam—Flamenco Beach in Culebra. A third POI 1020 along the personalizeditinerary is recommended by the EaaS platform 230 as “Miami SurfLessons” based on its location being along an existing route (from theuser-selected POI 1015 back to the port of New York 1005) and based on aprior recommendation that the EaaS platform 230 made for Jane, who theEaaS platform 230 determines is similar to Sam in that Jane alsoselected the second POI 1015, Flamenco Beach in Culebra (which is ashared trait between Sam and Jane).

While the recommended itinerary map interfaces 400, 500, 600, and 1000of FIG. 4, FIG. 5, FIG. 6, and FIG. 10 respectively, are all maps, itshould be understood that a personalized itinerary can take the form ofa list of POIs, either in order of when they should be visited or in adifferent order.

The resulting map interface 1000 illustrates a journey line 1080representing a path connecting the POIs 1005, 1010, 1015, 1020, and backto 1005, the journey line 1080 also connecting the current location 1030of the users. In some cases, a path 1080 may be somewhat pre-set, as ina pre-set cruise, in which case recommended POIs may be recommendedbecause they are along that path 1080 and one or more additionalreasons, such as similarity to “likes” of one or more of the users ordissimilarity to “dislikes” of one or more of the users or any of theother reasons identified above.

While various flow diagrams provided and described above may show aparticular order of operations performed by some embodiments of thesubject technology, it should be understood that such order isexemplary. Alternative embodiments may perform the operations in adifferent order, combine certain operations, overlap certain operations,or some combination thereof.

The foregoing detailed description of the technology has been presentedfor purposes of illustration and description. It is not intended to beexhaustive or to limit the technology to the precise form disclosed.Many modifications and variations are possible in light of the aboveteaching. The described embodiments were chosen in order to best explainthe principles of the technology, its practical application, and toenable others skilled in the art to utilize the technology in variousembodiments and with various modifications as are suited to theparticular use contemplated. It is intended that the scope of thetechnology be defined by the claim.

While the foregoing written description enables one skilled in the artto make and use what is considered presently to be the best modethereof, those skilled in the art will appreciate in light of thedisclosure that the existence of variations, combinations, andequivalents of the specific aspects, embodiments, structures, modules,methods, and examples herein. The disclosure should therefore not belimited by the above described examples, but by all aspects of thepresent teachings within the scope and spirit of the disclosure.

What is claimed is:
 1. A method for itinerary personalization for afirst venue attendee of a plurality of venue attendees in apredetermined venue area, the method comprising: receiving, from amobile device associated with the first venue attendee, a location ofthe mobile device associated with the first venue attendee; retrieving aplurality of venue attendee profiles including at least a first venueattendee profile corresponding to the first venue attendee and a secondvenue attendee profile corresponding to a second venue attendee, whereineach venue attendee profile identifies a plurality of traits about oneof the plurality of venue attendees; identifying that the first venueattendee is similar to the second venue attendee based on identifying atleast a first shared trait common to both the first venue attendeeprofile and the second venue attendee profile; retrieving locations of aplurality of points of interest located within the predetermined venuearea; selecting a recommended point of interest for the first venueattendee from the plurality of points of interest based on therecommended point of interest being within a predetermined range of thelocation of the mobile device associated with the first venue attendee,an indicator of positivity regarding the recommended point of interestand corresponding to the second venue attendee, and the prioridentification that the first venue attendee is similar to the secondvenue attendee; and sending at least the recommended point of interestto the mobile device associated with the first venue attendee.
 2. Themethod of claim 1, further comprising generating a personalizeditinerary including at least the recommended point of interest and asecond point of interest of the plurality of points of interest, whereinsending at least the recommended point of interest to the mobile deviceassociated with the first venue attendee includes sending thepersonalized itinerary to the mobile device associated with the firstvenue attendee.
 3. The method of claim 1, wherein identifying that thefirst venue attendee is similar to the second venue attendee is based onidentifying that the first venue attendee profile and the second venueattendee profile have a highest number of shared traits in commoncompared to a plurality of pairings of the first venue attendee profilewith each of the plurality of venue attendee profiles other than thefirst venue attendee profile.
 4. The method of claim 1, wherein thefirst shared trait common to both the first venue attendee profile andthe second venue attendee profile is a dietary restriction.
 5. Themethod of claim 1, wherein the first shared trait common to both thefirst venue attendee profile and the second venue attendee profile is anage group.
 6. The method of claim 1, wherein the first shared traitcommon to both the first venue attendee profile and the second venueattendee profile is an occupation.
 7. The method of claim 1, wherein thefirst shared trait common to both the first venue attendee profile andthe second venue attendee profile is an area common to a locationhistory of the mobile device associated with the first venue attendeeand a location history of a mobile device associated with the secondvenue attendee.
 8. The method of claim 1, further comprising receiving aselection by the first venue attendee of a selected point of interest ofthe plurality of points of interest from the mobile device associatedwith the first venue attendee, wherein the first shared trait common toboth the first venue attendee profile and the second venue attendeeprofile is selection of the selected point of interest.
 9. The method ofclaim 1, wherein the indicator of positivity about the recommended pointof interest corresponding to the second venue attendee is a rating bythe second venue attendee that exceeds a predefined thresholdcorresponding to positivity.
 10. The method of claim 1, wherein theindicator of positivity about the recommended point of interestcorresponding to the second venue attendee is a review by the secondvenue attendee that includes one or more phrases corresponding topositivity.
 11. The method of claim 1, wherein the indicator ofpositivity associated with the recommended point of interest andcorresponding to the second venue attendee is a selection of therecommended point of interest by the second venue attendee for anitinerary associated with the second venue attendee.
 12. The method ofclaim 1, wherein the indicator of positivity associated with therecommended point of interest and corresponding to the second venueattendee is a recommendation generated for the second venue attendee.13. The method of claim 1, wherein selecting the recommended point ofinterest for the first venue attendee from the plurality of points ofinterest is also based on the recommended point of interest fulfillingone or more requirements generated based on the first venue attendeeprofile, the one or more requirements associated with compliance withone or more preferences of the first venue attendee.
 14. The method ofclaim 1, wherein selecting the recommended point of interest for thefirst venue attendee from the plurality of points of interest is alsobased on the recommended point of interest fulfilling one or morerequirements generated based on the first venue attendee profile, theone or more requirements associated with avoidance of one or moredislikes of the first venue attendee.
 15. A system for itinerarypersonalization for a first venue attendee of a plurality of venueattendees in a predetermined venue area, the system comprising: acommunication transceiver that receives a location of a mobile deviceassociated with the first venue attendee and sends a recommended pointof interest to the mobile device associated with the first venueattendee; a memory that stores instructions, locations of a plurality ofpoints of interest located within the predetermined venue area, and aplurality of venue attendee profiles including at least a first venueattendee profile corresponding to the first venue attendee and a secondvenue attendee profile corresponding to a second venue attendee, whereineach venue attendee profile identifies a plurality of traits about oneof the plurality of venue attendees; and a processor, wherein executionof the instructions by the processor causes the processor to:identifying that the first venue attendee is similar to the second venueattendee based on identifying at least a first shared trait common toboth the first venue attendee profile and the second venue attendeeprofile, and selecting the recommended point of interest for the firstvenue attendee from the plurality of points of interest based on therecommended point of interest being within a predetermined range of thelocation of the mobile device associated with the first venue attendee,an indicator of positivity regarding the recommended point of interestand corresponding to the second venue attendee, and the prioridentification that the first venue attendee is similar to the secondvenue attendee.
 16. The system of claim 15, wherein the communicationtransceiver receives the location of the mobile device associated withthe first venue attendee from the mobile device associated with thefirst venue attendee.
 17. The system of claim 15, wherein thecommunication transceiver receives the location of the mobile deviceassociated with the first venue attendee from a point of sale (POS)terminal within the predetermined venue area.
 18. The system of claim15, wherein the communication transceiver receives the plurality ofvenue attendee profiles from one or more network servers.
 19. A methodfor itinerary personalization for a first venue attendee in apredetermined venue area, the method comprising: receiving a location ofa mobile device associated with the first venue attendee; storingprofile information identifying a first plurality of traits of the firstvenue attendee and a second plurality of traits of a second venueattendee; identifying a first shared trait that is common to both thefirst plurality of traits and the second plurality of traits; storinglocations of a plurality of points of interest located within thepredetermined venue area; selecting a recommended point of interest forthe first venue attendee from the plurality of points of interest basedon the recommended point of interest being within a predetermined rangeof the location of the mobile device associated with the first venueattendee, an indicator of positivity regarding the recommended point ofinterest and corresponding to the second venue attendee, and the prioridentification that the first venue attendee is similar to the secondvenue attendee; and sending at least the recommended point of interestto the mobile device associated with the first venue attendee.
 20. Themethod of claim 19, further comprising storing additional profileinformation identifying traits corresponding to a plurality of venueattendees other than the first venue attendee, wherein the second venueattendee is selected from the plurality of venue attendees other thanthe first venue attendee based on identifying the first shared traitthat is common to both the first plurality of traits and the secondplurality of traits.